Barron, Matthew

Esophageal diseases often necessitate resection of tissue. Current reconstruction options using autologous conduits such as stomach, colon, and small bowel have significant morbidity. Given these limitations in current therapy, we have developed a large animal model to regenerate short segments of esophageal tissue after circumferential full thickness resection. This is performed by implantation of an electrospun polyurethane tissue engineered graft which results in esophageal regrowth. These implantations have been performed both with cell based seeding the polymer scaffold and without with comparable regenerative results. It is possible that esophageal regeneration in this model has unequal contributions from either the proximal or distal esophagus. To determine preferential directionality of regeneration we aim to utilize biomechanical markers to suggest that there are unequal proximal and distal contributions to regenerated tissue. Given limited availability of regenerated tissue, use of a non‐destructive method to perform this testing would have significant utility. Through using our previously validated non‐destructive sonometric ex vivo method we aim to determine differences in mechanical behavior of the regenerated tissue in comparison to proximal and distal esophageal tissues. Using this method we are able to determine longitudinal and circumferential moduli and derive strain energy functions and parameters. Within this work we demonstrate that there are differences in mechanical behavior and that the regenerated tissue behaves more comparably to proximal esophageal tissue suggesting preferential regrowth and unequal contribution to regenerated tissue. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

AbstractMost FDA‐approved drugs are not equally effective in all patients, suggesting that identification of biomarkers to predict responders to a chemoprevention agent will be needed to stratify patients and achieve maximum benefit. The goal of this study was to investigate both patient‐specific and cell context‐specific heterogeneity of metformin response, using fibroblast cell lines and induced pluripotent stem cells differentiated into lung epithelial lineages. We performed cell survival analysis, transcriptome and whole exome sequencing analysis on both patient‐derived cell lines and cancer cell lines to assess differential metformin response and identify response genes. We found differences in response to metformin treatment across a variety of cell lines and cellular contexts, suggesting that heterogeneity may be patient‐ and cell type‐specific. Gene expression profiling and analysis of metformin‐sensitive and metformin‐resistant cells identified differentially expressed genes that may be able to stratify patients into metformin responders and non‐responders. Sequencing analysis found genomic alterations that correlated with metformin response. These results suggest that the identification of genomic biomarkers for patients who may respond to metformin treatment can provide an opportunity for individualizing metformin chemoprevention in the clinical setting.

Abstract Background: Squamous cell carcinoma is a common type of lung cancer and accounts for about 25-30% of all non-small cell lung cancers. Metformin is a drug commonly prescribed as first-line treatment for type-2 diabetes, with some evidence showing that the drug can also act directly on cancer cells. One of the mechanisms of action is through activation of the AMP-activated protein kinase (AMPK) which is involved in control of energy homeostasis in cells. The goal of this study was to determine metformin response in different cell lines and different cellular contexts, and to use that information to work towards the generation of a metformin “sensitivity index” that could be used guide individualized chemoprevention. Methods: We performed cell survival analysis on squamous cell carcinoma lines, skin fibroblast lines and differentiated IPS cell lines to identify differences in metformin response both for different cell lines and for cells in different cell context. Microarray profiling was used to determine differentially expressed genes that are regulated by metformin treatment in order to generate signatures of metformin response. Results: Cell survival analysis showed that different cell lines respond differently to metformin, and cells of identical genotypes in a variety of differentiated states or cellular contexts also show differential response to metformin. Gene expression profiling of metformin treated cells identified differentially expressed genes that may mediate metformin response. Conclusion: Differences in response to metformin treatment across a variety of cell lines and cellular contexts suggest heterogeneity that may be patient-specific. Using genes that are differentially expressed following metformin treatment, we identified a 55-gene set that can be used as a metformin “sensitivity index” to stratify patients into metformin responders and non-responders and guide individualized chemoprevention. Citation Format: Michael K. Asiedu, Matthew R. Barron, Marie Christine Aubry, Dennis Wigle. Metformin as a chemoprevention agent for lung squamous cancer. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 1897. doi:10.1158/1538-7445.AM2015-1897